Number Of Spectrum Handoff Research Articles

Intelligent Dynamic Spectrum Resource Management Based on Sensing Data in Space-Time and Frequency Domain.

Edge computing offers a promising paradigm for implementing the industrial Internet of things (IIoT) by offloading intensive computing tasks from resource constrained machine type devices to powerful edge servers. However, efficient spectrum resource management is required to meet the quality of service requirements of various applications, taking into account the limited spectrum resources, batteries, and the characteristics of available spectrum fluctuations. Therefore, this study proposes intelligent dynamic spectrum resource management consisting of learning engines that select optimal backup channels based on history data, reasoning engines that infer idle channels based on backup channel lists, and transmission parameter optimization engines based genetic algorithm using interference analysis in time, space and frequency domains. The performance of the proposed intelligent dynamic spectrum resource management was evaluated in terms of the spectrum efficiency, number of spectrum handoff, latency, energy consumption, and link maintenance probability according to the backup channel selection technique and the number of IoT devices and the use of transmission parameters optimized for each traffic environment. The results demonstrate that the proposed method is superior to existing spectrum resource management functions.

Joint Clustering Method and Reinforcement Learning-Based Spectrum Management in Mobile Cognitive Radio Networks

The spectrum management scheme is a crucial issue to utilize the limited resource and secure a higher quality of performance in mobile cognitive radio networks. We propose a spectrum management method to utilize the spectrum effectively and minimize the communication cost in mobile cognitive radio networks. We consider the following parts such as statistical information about spectrum access patterns and the number of spectrum hand-off. In addition, this paper proposes to make the parameters to decide the spectrum access of the secondary user during the primary user doesn’t use it. Those parameters are based on dynamic clustering and reinforcement learning. However, both the dynamic clustering method and reinforcement learning haven’t been studied much to minimize communication costs in mobile cognitive radio networks. Firstly, our study is to improve the opportunity of spectrum access through the analysis based on the spectrum patterns and the number of both the secondary user and the primary user in mobile cognitive radio networks. Secondly, we decrease the number of hand-offs because it checks the status of the available channel and the patterns of the spectrum usage in the clustering. Above all, the improvement of this paper is to cut down the cost of communication by utilizing the way of the optimal spectrum access in mobile cognitive radio networks.

Spectrum-aware cross-layered routing protocol for cognitive radio ad hoc networks

Cognitive radio network has been proposed as a promising technology to satisfy the manifold requirements of future generation (5G) wireless system by intelligently accessing the underutilized channel of a primary user. However, due to the heterogeneity in channel propagation characteristics, intermittent availability of licensed channel, recurrent hand-offs, and need of a protection to primary users, finding a successful route is more challenging. Also, incorporation of opportunistic spectrum access in cognitive radio network requires a potential spectrum management functions across the network layers. Hence, a cross-layered channel assignment algorithm and routing algorithm is proposed for a cognitive radio ad hoc network which can overcome above-mentioned challenges and provide a stable path for routing of data packets. A novel metric, for the probability of successful transmission of a channel is derived by considering channel statistics, sensing periodicity of the cognitive user, and time-varying channel quality. Also, the number of available channels and their characteristics is considered for the selection of a next-hop node with an aim to avoid the one-hop neighbors located in the PU transmission range. The proposed routing protocol is simulated in ns-2 and compared with the existing similar protocols. The performance shows that the proposed algorithm performs better in terms of throughput, end-to-end delay, number of spectrum hand-offs, and interference to the primary user in a significant manner.

A delay-aware spectrum handoff scheme for prioritized time-critical industrial applications with channel selection strategy

Cognitive radio has emerged as an enabling technology in the realization of a spectrum-efficient and delay-sensitive industrial wireless communication where nodes are capable of responding in real-time. However, particularly for time-critical industrial applications, because of the link-varying channel capacity, the random arrival of a primary user (PU), and the significant delay caused by spectrum handoff (SH), it is challenging to realize a seamless real-time response which results in a quality of service (QoS) degradation. Therefore, the objectives of this paper is to increase spectrum utilization efficiency by allocating channel based on the priority of a user QoS requirements, to reduce SH delay, to minimize latency by preventing avoidable SHs, and to provide real-time response. To achieve an effective spectrum utilization, we proposed an integrated preemptive/non-preemptive priority scheme to allocate channels according to the priority of user QoS requirements. On the other hand, to avoid significant SH delays and substantial latency resulting from random PU arrival, a unified spectrum sensing technique was developed by integrating proactive sensing and the likelihood estimation technique to differentiate between a hidden and a co-existence PU, and to estimate the mean value of the busy and the idle periods of a channel respectively. Similarly, to prevent poor quality channel selection, a channel selection technique that jointly combines a reward system that uses metrics, e.g. interference range, and availability of a common channel to ranks a set of potential target channels, and a cost function that optimizes the probability of selecting the channel with the best characteristics as candidate channels for opportunistic transmission and for handoffs was developed. The simulation results show a significant performance gain of the delay-PritSHS in terms of number of SHs, Latency, as well as throughput for time-critical industrial applications in comparison to other schemes.

Fuzzy Based PC-PUSH in CR-MANETs

In cognitive radio (CR), the secondary user (SU) needs to hand off its ongoing communication to an idle channel in order to avoid interference to the primary user (PU). Spectrum hand off issue becomes challenging in CR mobile ad hoc networks (CR-MANETs) because of the uncertainty in spectrum availability, broad range of spectrum bands and lack of central entity. The purpose of this study is to design a unified spectrum handoff (USH) scheme for CR-MANETs that considers the spectrum heterogeneity and its availability over time and space. A local flow hand off is performed when spectrum hand off cannot be carried out due to the SUs mobility. To improve further USH, preemptive unified spectrum handoff (PUSH) algorithm is proposed in which two different preemptive hand off threshold regions are defined. The PUSH algorithm also predicts the cognitive link availability considering the PU interference boundary. Although the PUSH scheme improves the hand off performance, the number of spectrum hand offs due to the PU activity should be reduced in this scheme. Therefore, the PC-PUSH (Power Controller-PUSH) scheme is proposed in which the fuzzy logic is used to improve the PUSH in terms of the number of spectrum handoffs because of the PU activity. The PC-PUSH decreases the interference to the PUs, while reducing the number of spectrum handoffs. The results show that the proposed scheme improves the link maintenance probability, decreases the hand off delay, and reduces the number of spectrum handoffs.

Sequential sensing based spectrum handoff in cognitive radio networks with multiple users

Spectrum handoff occurs when the primary users appear in the licensed spectrum temporarily occupied by the secondary users and aims to help the secondary users to vacate the spectrum rapidly and to resume transmission on new selected available channels. However, a spectrum handoff policy that comprehensively considers spectrum sensing, target channel selection as well as spectrum estimation has yet to be developed. In this paper we present a sequential sensing based spectrum handoff policy for multiple-user cognitive radio networks. First, we select the appropriate candidate channels for each secondary user, then their associated optimal sensing order together with the best target handoff channel is determined through sequential sensing based on Dynamic Programming (DP). Note that many spectrum handoff will occur during one secondary user transmission and our objective is to minimize the total number of spectrum handoff. The sequential sensing based spectrum handoff policy is evaluated through a comprehensive simulation study. The results reveal significant improvements in the system performance by reducing the number of spectrum handoff over conventional approaches. Moreover, our proposed DP method can significantly lower the computational complexity compared to exhaustive search and common DP (performing sequential sensing over all the channels in the system using Dynamic Programming).